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16 articles for “chest X-ray”
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Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.
Abstract: Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 13–21 Read article
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Automatic Chest X-ray Report Generation Using Machine Learning
Abstract: In this study, a deep neural network is suggested for the automatic creation of precise radiologist reports from chest X-ray pictures. The proposed network responds to the need for medical image captioning by learning to extract key features from the image and creating tag embeddings for each patient's X-ray images. Medical image captioning demands coherence and high accuracy in identifying abnormalities and extracting information. For a finer representation, the network …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 1, 2023 · pp. 29–39 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Parry–Romberg Syndrome in A Young Male
Abstract: Parry–Romberg syndrome is a condition in which there is slow and progressive shrinkage of the tissues and sometimes bones of one or occasionally both sides of the face. We report a rare case of Parry-Romberg syndrome with trigeminal neuralgia in a 27 year old male with complaints of right sided headache (on and off) and right sided facial pain, which was intermittent and progressive in nature since past 6 months. …
Published in Research and Reviews: A Journal of Dentistry · Vol. 6, Issue 1, 2015 · pp. 14–17 Read article
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Sustainable and Smart Solutions Utilizing Feature Descriptors Analysis
Abstract: Neighborhood highlight locators and descriptors (hereinafter extractors) play a key part within the cutting-edge computer vision for developing smart solutions. Their scope is to extricate, from any picture, a set of discriminative designs (hereinafter key points) show on a few parts of foundation and/or closer view components of the picture itself. A prerequisite of a wide run of down to earth applications (e.g., vehicle following, individual re-identification) is the plan …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 3, 2022 · pp. 35–40 Read article
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Accidentally Diagnosed Hepatic Hydatid Cyst: A Case Report
Abstract: Hydatid disease is a parasitic infection by a tape worm of Genus Echinococcus. It is a zoonotic disease that occurs throughout the world. The life cycle of E. granulosus alternates between herbivores and carnivores (Such as sheep & Dogs). Man is an accidental intermediate host and a dead end in parasites life cycle. The oral entry of parasite finds its host organ as intestinal mucosa where they develop into adult …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 10, Issue 2, 2021 · pp. 1–4 Read article
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Rare Three Cases of Right Sided Diaphragmatic Rupture Following Blunt Trauma Abdomen
Abstract: Diaphragmatic rupture can occur with both blunt trauma chest as well as blunt trauma abdomen which can be associated with herniation of abdominal content into thoracic cavity. Diaphragmatic injury is common following chest injury in 1–7% cases but it's rare following blunt trauma abdomen. In this study we had seen three cases in which there was rupture of diaphragm due to blunt trauma abdomen without any rib fracture and wound …
Published in Research and Reviews : Journal of Surgery · Vol. 4, Issue 2, 2015 · pp. 17–19 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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AI in Healthcare: Drug Delivery in Tuberculosis
Abstract: Tuberculosis (TB) , mainly caused by Mycobacterium tuberculosis, remains a major global health burden, accounting for millions of new infections and deaths each year. Although progress has been made in diagnosis and treatment, the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB makes disease control increasingly difficult. Conventional diagnostic approaches such as chest X-rays, sputum smear microscopy, and culture methods continue to play an important role, but they …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 9–17 Read article
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Pneumonia Detection Using Deep Learning–Convolutional Neural Network
Abstract: Pneumonia disease is associate in nursing infectious and deadly illness in metabolic process that is caused by microorganism, fungi, or a deadly disease that infects the human respiratory organ air sacs with the load choked with fluid or pus. Chest X-rays area unit the common methodology accustomed diagnose respiratory disorder and it wants a health worker to gauge the results of X-ray. The hard methodology of detection of the respiratory …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 9–16 Read article
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Incidence of Scrofula in Enlarged Neck Nodes
Abstract: To determine the incidence of scrofula (tubercular lymphadenitis) in enlarged neck nodes, prospective study is carried out in the Department of General Surgery, NIMS Medical College, Jaipur for three years from June 2011 to May 2014. The study included a group of 130 patients with cervical lymphadenopathy. All patients were clinically examined and investigated thoroughly. CBC, ESR, X-ray chest and Montoux’s test were performed. Fine Needle Aspiration Cytology (FNAC) and …
Published in Research and Reviews : Journal of Surgery · Vol. 3, Issue 3, 2014 · pp. 5–8 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Federated Learning for Privacy-Preserving AI Model Training Across Distributed Healthcare Systems
Abstract: Building effective AI diagnostic tools in clinical environments presents a fundamental contradiction — the patient data most critical to model performance is precisely the data subject to the strictest legal and institutional restrictions. Regulations such as HIPAA and GDPR, while essential for protecting patient rights, render conventional centralized training pipelines largely impractical in real hospital settings where data cannot be transferred, pooled, or shared across institutional boundaries. This paper presents …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article